```
import numpy as np
import pandas as pd
data = [[30, 19, 6], [12, 23, 14], [8, 18, 20]]
df = pd.DataFrame(data = data, index = ['A', 'B', 'C'], columns = ['Bulgary', 'Robbery', 'Car Theft'])
df
```

I get the following:

Bulgary | Robbery | Car Theft | |
---|---|---|---|

A | 30 | 19 | 6 |

B | 12 | 23 | 14 |

C | 8 | 18 | 20 |

I would like to assign:

```
df['Total'] = df['Bulgary'] + df['Robbery'] + df['Car Theft']
```

But does this operation have to be done manually? I am looking for a function that can handle conveniently.

```
#pseudocode
#df['Total'] = df.Some_Column_Adding_Function([0:3])
#df['Total'] == df['Bulgary'] + df['Robbery'] + df['Car Theft'] returns True
```

- Similarly, how do I add across rows?

### >Solution :

Use `sum`

:

```
df['Total'] = df.sum(axis=1)
```

Or if you want subset of columns:

```
df['Total'] = df[df.columns[0:3]].sum(axis=1)
# or df['Total'] = df[['Bulgary', 'Robbery', 'Car Theft']].sum(axis=1)
```